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Data Science


Autocorrelation is a measure of the degree of similarity between any time series and a lagged or offset version of itself over successive time intervals.

Business Intelligence

Business Intelligence allows companies to make data-driven decisions.

Data Drift

Data Drift is the phenomenon where changes to data degrade model performance.

Data Mining

Data Mining is a process applied to find unknown patterns, correlations, and anomalies in data. Through mining, meaningful insights can be extracted from data.

Data Pipelines

Data pipelines are processes that result in the production of data products, including datasets and models.

Directed Acyclic Graphs

If you don’t know your DAGs from your dogs, you can finally get some clarity and sleep easily tonight. Learn what makes a Directed Acyclic Graph a DAG.

Discrete vs Continuous Time

In continuous time, variables may have specific values for only infinitesimally short amounts of time. In discrete time, values are measured once per time interval.

Graph Databases

Graph Databases are a type of database that emphasizes the relationships between data.

Knowledge Graphs

Knowledge Graphs contextualize data and power insight generation.

Machine Learning

Machine Learning is a subfield of Artificial Intelligence where parameters of an algorithm are updated from data inputs or by interacting with an environment.


Metadata is data about data. It’s quite simple, really. Learn more about how it’s used within.

Model Drift

Models tend to become less accurate over time.


Parameters control specific parts of a system's behavior.

Process Mining

Process mining is an application of data mining with the purpose of mapping an organization’s processes. It is used to optimize operations, and identify weaknesses.


Robustness is a measure of a model's accuracy when presented with novel data.


Schemas are descriptions of things: agents in simulations, and the actions they take. They help make simulations interoperable, and data more easily understood.

Single Synthetic Environment

Single synthetic environments allow you to build, run, and analyze data-driven models and simulations.


Stochasticity is a measure of randomness. The state of a stochastic system can be modeled but not precisely predicted.

Time Series Data

Time series data is data that has been indexed, listed, or graphed in time order. For example, the daily closing value of the NASDAQ, or a single step in a simulation run.